Abstract: A method for identifying a body motion includes receiving a series of images including a visual presentation of a human face from the image capture device. The series of images may form an image sequence. Each of the series of images may have a previous image or a next image in the image sequence. The method also includes, for each of the series of images, determining a plurality of characteristic points on the human face, determining positions of the plurality of characteristic points on the human face, and determining an asymmetry value based on the positions of the plurality of characteristic points. The method further includes identifying a head-shaking movement of the human face based on the asymmetry values of the series of images.

Abstract: The present disclosure relates to a system and a method for distinguishing a driver and passengers in an image captured inside a vehicle. The system may perform the method to: obtain a face set from the image, the face set including at least one human face inside the vehicle and coordinates of the at least one human face; obtain a candidate driver face set from the face set based on the coordinates of the at least one human face, the candidate driver face set including at least one candidate driver face and coordinates of the at least one candidate driver face; and identify a target driver face from the at least one candidate driver face based on the coordinates of the at least one candidate driver face.

Abstract: The present disclosure relates to systems and methods for automated identification of presence of a facial action from sequential images. The systems and methods may obtain a plurality of sequential candidate image frames containing a facial object. Each of the plurality of candidate image frames may include a plurality of feature points associated with an eye of the facial object. For each of the plurality of sequential candidate image frames, the systems and methods may determine an area of a polygon based on the plurality of feature points. The systems and methods may determine a distance associated with the eye of the facial object. The systems and methods may determine an action parameter based on the area and the distance. The systems and methods may identify the presence of a blink action in response to that the action parameters satisfy one or more preset conditions.

Abstract: The present disclosure relates to systems and methods for action recognition. The systems and methods may obtain a plurality of sequential target image frames associated with facial information of an object. Each of the plurality of sequential target image frames may include a plurality of feature points associated with the facial information. The systems and methods may determine a first area and a second area based on the plurality of feature points in each of the plurality of sequential target image frames. The systems and methods may determine an asymmetry parameter in each of the plurality of sequential target image frames based on the first area and the second area. The systems and methods may identify a shaking action in response to that the asymmetry parameter satisfies a preset condition.

Abstract: A method for identifying a body motion includes receiving a series of images including a visual presentation of a human face from the image capture device. The series of images may form an image sequence. Each of the series of images may have a previous image or a next image in the image sequence. The method also includes, for each of the series of images, determining a plurality of characteristic points on the human face, determining positions of the plurality of characteristic points on the human face, and determining an asymmetry value based on the positions of the plurality of characteristic points. The method further includes identifying a head-shaking movement of the human face based on the asymmetry values of the series of images.

Abstract: The present disclosure relates to systems and methods for automated identification of presence of a facial action from sequential images. The systems and methods may obtain a plurality of sequential candidate image frames containing a facial object. Each of the plurality of candidate image frames may include a plurality of feature points associated with an eye of the facial object. For each of the plurality of sequential candidate image frames, the systems and methods may determine an area of a polygon based on the plurality of feature points. The systems and methods may determine a distance associated with the eye of the facial object. The systems and methods may determine an action parameter based on the area and the distance. The systems and methods may identify the presence of a blink action in response to that the action parameters satisfy one or more preset conditions.

Abstract: The present disclosure relates to systems and methods for action recognition. The systems and methods may obtain a plurality of sequential target image frames associated with facial information of an object. Each of the plurality of sequential target image frames may include a plurality of feature points associated with the facial information. The systems and methods may determine a first area and a second area based on the plurality of feature points in each of the plurality of sequential target image frames. The systems and methods may determine an asymmetry parameter in each of the plurality of sequential target image frames based on the first area and the second area. The systems and methods may identify a shaking action in response to that the asymmetry parameter satisfies a preset condition.

Abstract: An embodiment of the present disclosure discloses a testing device and a method thereof, wherein the method specifically includes: determining the number of chromatic dispersion pixel points in a target image; wherein the target image is an image generated after being output onto a screen by a preset preprocessing algorithm and passing through a lens, and the preset preprocessing algorithm is used for performing preprocessing on an image in a virtual reality helmet; determining a ratio of the chromatic dispersion pixel points to total pixel points of the target image according to the number of the chromatic dispersion pixel points; and determining a chromatic dispersion degree of the target image according to the ratio. The embodiment of the present disclosure may realize the testing of a preprocessing result of the preprocessing algorithm.

Abstract: Some embodiments of the present disclosure provide an image preprocessing method and an image preprocessing device for image registration. The method includes: selecting a Gaussian filtering window size and a Gaussian filtering smoothness parameter for constructing a Gaussian filtering function; calculating first order partial derivatives of the Gaussian filtering function in different directions respectively; performing convolution operation on the first order partial derivatives in different directions with original images in corresponding directions and images to be registered in corresponding directions respectively, and obtaining filtered original images and filtered images to be registered in corresponding directions; and performing image registration on the filtered original images and the filtered images to be registered. denoising by filtering during image registration is implemented, and the image registration precision is improved.